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Record W2016701923 · doi:10.1177/1087054712443157

Duloxetine in Adults With ADHD

2012· article· en· W2016701923 on OpenAlexaff
Mathieu Bilodeau, Tarek Simon, Miriam H. Beauchamp, Paul Lespérance, Simon Dubreucq, Jean-Pierre Dorée, Smadar Valérie Tourjman

Bibliographic record

VenueJournal of Attention Disorders · 2012
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsInstitut universitaire en santé mentale de MontréalCentre Hospitalier de l’Université de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité LavalUniversité de Montréal
Fundersnot available
KeywordsDuloxetineHamilton Anxiety Rating ScaleClinical Global ImpressionRating scalePsychologyPlaceboAnxietyDepression (economics)Clinical psychologyPsychiatryMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the effect of duloxetine on ADHD in adults. METHOD: In a 6-week double-blind trial, 30 adults with ADHD received placebo or duloxetine 60 mg daily. The Conners' Adult ADHD Rating Scale (CAARS) and the Clinical Global Impression Scales (CGI) were used to assess symptom severity and clinical improvement. The Hamilton Anxiety Rating Scale (HARS) and the Hamilton Depression Rating Scale (HDRS) were used to measure the effect on anxiety and depressive symptoms. RESULTS: The Duloxetine group showed lower score on CGI-Severity at Week 6 (3.00 vs. 4.07 for placebo, p < .001), greater improvement on CGI-Improvement (2.89 vs. 4.00 at Week 6, p < .001), and greater decreases on five of eight subscales of the CAARS. There was no treatment group effect on HDRS or HARS scores. CONCLUSION: Duloxetine may be a therapeutic option for adults with ADHD, but further studies are required to replicate these findings in larger samples.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.299
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2012
Admission routes1
Has abstractyes

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Same venueJournal of Attention DisordersSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207